Cancer Treatment Before and After Physician-Pharmacy Integration

This cohort study examines the implications of physician-pharmacy integration for the use of, cost of, and adherence to anticancer drugs among patients with late-stage cancer.


eAppendix 2. Patient attribution to physicians and oral drugs in sample
Patients were attributed to a primary oncologist each year based on physician share of medical and pharmacy claims.Because of our focus on oral drug prescribing, we attributed patients to a primary oncologist based on, first, who prescribed a plurality of a patient's pharmacy claims for 41 common oral anticancer drugs (see Table A2a below).If there were no oral therapy claims, we attributed patients to the oncologist associated with a plurality of medical claims for physicianadministered anticancer therapies and oncology-related Evaluation and Management visits.Additional protocol details are described in Kanter et al.    , is the outcome for physician i in cohort c in year y at t years pre/post-integration;    is a binary variable indicating whether the physician i is an integrating physician;     is a binary variable indicating whether the year y is at or after the year of integration for integrating cohort c;      is a variable that assumes the value 1 in any year y that is t years pre/postintegration for cohort c, and 0 otherwise; and   is a vector of characteristics of physician i in year y.
The coefficient  identifies the DD parameter for average treatment-on-the-treated for cohort c at t years post-integration, ATT(c,t).This specification reflects the standard 2x2 DD setup, where the comparison group was the set of physicians who had not (yet) integrated with pharmacies by year y.
To obtain an estimate of the overall effect of pharmacy integration, ATT(c,t) estimates were aggregated over all integrating cohorts c and post-integration years t, as described in Callaway and Sant'Anna. 2Standard errors were clustered at the physician level to account for autocorrelated errors associated with observing the same physician across multiple time periods.Aggregation of ATT(c,t) and clustering of standard errors via multiplier bootstrapping were conducted as described in Callaway and Sant'Anna.

Tests of parallel trends assumption
To assess the plausibility of the parallel trends assumption, we applied the test of parallel trends described in Callaway and Sant'Anna.For our analysis, the null hypothesis was no difference in trends in the 3 years prior to physician-pharmacy integration between practices that integrated and practices that did not.Note that this test is conservative and over-rejects the null hypothesis of no parallel trends.
We conducted tests for unconditional parallel trends--the assumption required for the DD analysis without covariates--and tests for conditional parallel trends--the assumption required for the DD analysis with covariates.Note that it is unlikely for both assumptions to simultaneously be true.If unconditional parallel trends holds-i.e., if there were no difference in the pre-period trends between integrating and non-integrating oncologists-then conditional parallel trends-i.e., parallel pre-period trends conditional on covariates-is unlikely to hold unless the covariates themselves are trending in the same way (even more unlikely).Also note that if parallel trends in levels of expenditures holds, then it is unlikely that parallel trends in log-transformed expenditures also holds, although the test may not be sufficiently powered to reveal that difference.
For each outcome of interest, the Χ 2 statistic for the test and its associated p-value are reported below.For most outcome measures for the aggregated cancer site sample (full sample), we could not reject the null hypothesis that there was no difference in trends between integrating practices and non-integrating practices in the years prior to integration.Log-transformed expenditure outcomes were closer to the rejection threshold than level expenditures outcomes.
The null hypothesis of no difference in pre-integration trends was rejected more frequently for outcomes associated with the breast cancer sample and for tests of the conditional parallel trends assumption, i.e., the assumption that trends in outcomes are parallel conditional on the covariates.Note: Point estimates with 95% CI bars for outcomes in each year indexed to year of integration (t=0).Blue markers and lines show pre-integration years and red markers and lines show post-integration years.Deviations from x-axis at 0 reflect differences between integrating oncologists and non-integrating oncologists.

Change in utilization and expenditures following pharmacy integration, difference- in-differences estimates with covariates
Note that the number of physicians in the Total column is the number of unique physicians in the full sample.This total is not the sum of the annual number of physicians because different physicians enter and exit the sample in different years throughout the sample period.

Change in expenditures and share of patients prescribed oral drugs, by therapeutic category: oral chemotherapy, oral hormone therapy, oral targeted therapy, oral supportive care
p<0.10 ** p<0.05 ***p<0.01 *